This technology calculates distance by comparing the size of an object projected in an image captured by a monocular camera with the pre-set physical dimensions of the actual object. It then generates circular band regions by applying differential error ranges based on the object's position within the image, and estimates the current position of the moving object through the overlapping sections of these regions.
In environments using only a monocular camera, issues with uncertainty in accurate distance estimation and reduced precision in position tracking within complex environments have been persistent challenges.
This technology calculates the distance to each object using the width of the projected object in the image, the camera's focal length, and the actual width of the object. It sets varying error ranges based on the projected object's position to construct circular bands centered on the actual object's coordinates, then identifies the position through the intersecting areas. Applicable to autonomous robots, service robots, and logistics transport platforms, it enhances the accuracy and reliability of position estimation in complex environments using only a single camera.
This invention was developed with the support of the Ministry of Science and ICT's AI Convergence Innovation Talent Cultivation program.
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